A replication study: mining a proprietary temporal defect dataset

We conduct a replication study to define temporal patterns of activity sequences in a proprietary dataset, and compare them with an open-source dataset. Temporal bug repository data may give many insights in the context of root-cause analysis of defects. Observing activities based on temporal changes enables the formation of temporal activity sequences. We use datasets from an issue tracking system repository of a proprietary and enterprise level software life-cycle management tool. We define the temporal patterns of activity sequences and compare them with Firefox data. On the basis of these analyses, we observe that some activities of the sequences are more critical than the others in the context of proprietary projects. Similarities and differences of the relevant activities are highlighted and explained. Integrating results from various empirical studies helped us in gradually generalizing evidences observed in the original study, and identifying the consistencies between open-source projects and proprietary ones. Comprehending temporal activity sequences assist software quality teams to optimize the allocation of their human resources as well on manage project schedules more efficiently.